Evidence map›Paper›PMID 40592910›Full record

ArticleScientific reports2025

Impact of low carbon orientation on green finance in highly polluted areas based on STIRPAT spatial panel model.

Yunyan Yang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Yunyan YangSchool of Finance, Tongling University, Tongling, 244061, China. yangyunyan1988@163.com.

Funding

Anhui Province University Research Program Project 2022AH051730
6 · The paper itself

Abstract

In the context of the current global economic transformation, the integration of low-carbon economy and green finance has become a core issue in promoting sustainable development. This study focuses on the development of low-carbon finance in high pollution areas and explores its promoting effect on green finance. This study aims to analyze the impact of low-carbon orientation on green finance, clarify the intrinsic relationship between the two, and provide strategic recommendations for the development of low-carbon emission reduction finance in high pollution areas. To achieve the research objectives, this study used a random effects regression model and a spatial panel data model to conduct in-depth analysis of the carbon emission index in high pollution areas. The research results show that the Geary carbon emission C index in high pollution areas is significantly less than 0, indicating a negative correlation between carbon emissions and spatial distribution. The parameter values for financial scale and efficiency are 0.2031, 0.1125 and - 0.0089, 0.5365, respectively, while the parameter values for green finance are - 0.4154 and 0.0176. These data indicate that low-carbon policies have a significant promoting effect on green finance. The findings of this study have important practical significance for the development of green finance in high pollution areas. Given that green finance in the region is still in its infancy, research suggests further implementation of low-carbon emission reduction policies to promote the healthy growth of green finance and achieve dual benefits of economy and environment.

Indexed as

Green financeLow carbon orientationSpatial panel dataSTIRPAT model

Identifiers

PMID40592910
PMCPMC12214895

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.